Data Analysis and Interpretation
Once the large data sets have been collected, we are required to extract the new physics information from them. As experiments and therefore data are very expensive it is important this is done to the highest standard. Currently our group works at the junction between experimental data, phenomenological interpretation, and statistical analysis. This provides the opportunity for students to develop high level mathematical and computational skills in the context of QCD. We are currently driving the use of Bayesian analysis techniques in hadron physics analysis as well as utilising other big data methods such as neural networks and computer learning. Students with more theoretical interests would be welcome to pursue a more theoretical project through our collaboration with JPAC, an international QCD phenomenology centre.